Lead Data & Integration Engineer

Lead Data & Integration Engineer Important Information Location: Singapore Key Responsibilities 1. System Analysis & Design • Analyse business/technical requirements and translate them into data flows and integration designs • Work with upstream and downstream teams to define data contracts and interfaces • Identify gaps, inefficiencies and risks in current data movement processes • Propose pragmatic solutions balancing speed, quality and maintainability • Integration & Data Movement • Design and implement data movement across systems using: • APIs • SFTP and file based transfers • Batch pipelines • Coordinate integrations across systems in the DataLake ecosystem (Informatica, Cloudera, etc.) • Ensure data is correctly transformed, mapped and delivered to target systems • Troubleshoot integration issues across environments • Data Preparation for GenAI • Support data ingestion and preparation for GenAI use cases: • document ingestion • data aggregation • enrichment and transformation • Work with structured and unstructured data • Ensure data is usable for downstream AI workflows (RAG, search, investigation flows) You are not asking them to build models, just make data usable for them. • Delivery & Coordination • Work across multiple teams: • data platforms • application teams • infrastructure • security • Support SIT, UAT and production rollouts • Ensure integration reliability, error handling and monitoring • Document flows, mappings and interfaces clearly Key Requirements Below are the key skillsets that will be required for all relevant tasks mentioned: • 10 years of experience in system analysis, integration engineering, data engineering or technical delivery roles. • Strong ability to translate requirements into system flows, data flows, interface specifications and implementation plans. • Experience working with upstream and downstream teams to define and deliver enterprise integrations. • Practical experience with REST APIs, SFTP, batch processing, file based integration and data pipeline orchestration. • Good understanding of data mapping, transformation, aggregation, reconciliation and data quality controls. • Good SQL skills and basic to moderate Python skills for data handling, scripting, automation and troubleshooting. • Exposure to Java • Exposure to Informatica, Cloudera or similar enterprise data platforms. • Working knowledge of Git , branching, pull requests, code reviews and controlled release practices. • Familiarity with CI/CD, Jira, Confluence and enterprise deployment processes. • Experience with Control M or equivalent scheduling tools. • Familiarity with logging (OTEL) and monitoring tools such as Splunk Elastic Stack. • Exposure to GenAI concepts such as document ingestion, RAG, embeddings and data preparation for AI workflows. • Strong communication skills, with the ability to challenge weak designs and coordinate across business, application, data, infrastructure and security teams. Key Domain: • Data Engineering, • System Integrations, • Python, SQL About Encora Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others. At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality